![Dimensions in Arrays
A dimension in arrays is one level of array depth
1-D Arrays
An array that has 0-D arrays as its elements is called
uni-dimensional or 1-D array.These are the most
common and basic arrays.
import numpy as np
arr = np.array([1, 2, 3, 4, 5])
print(arr)](https://image.slidesharecdn.com/numpy-200828122621/85/Numpy-7-320.jpg)
![2-D Arrays
An array that has 1-D arrays as its elements is called a
2-D array.These are often used to represent matrix or
2nd order tensors.
import numpy as np
arr = np.array([[1, 2, 3], [4, 5, 6]])
print(arr)](https://image.slidesharecdn.com/numpy-200828122621/85/Numpy-9-320.jpg)
![3-D arrays
An array that has 2-D arrays (matrices) as its elements
is called 3-D array.These are often used to represent a
3rd order tensor.
import numpy as np
arr = np.array([[[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]]])
print(arr)](https://image.slidesharecdn.com/numpy-200828122621/85/Numpy-10-320.jpg)
![INITIALIZTION
np.array([1,2,3]) 1d array
np.array([(1,2,3),(4,5,6)]) 2d array
np.arange(start,stop,step) range array
np.linspace(0,2,9)
Add evenly spaced values btw interval to array of
length
np.zeros((1,2)) Create and array filled with zeros
np.ones((1,2)) Creates an array filled with ones
np.random.random((5,5)) Creates random array
np.empty((2,2)) Creates an empty array](https://image.slidesharecdn.com/numpy-200828122621/85/Numpy-11-320.jpg)
![Operations
Operator Description
np.add(x,y)
x + y
Addition
np.substract(x,y)
x – y
Subtraction
np.divide(x,y)
x / y
Division
np.multiply(x,y)
x @ y
Multiplication
np.sqrt(x) Square Root
np.sin(x) Element-wise sine
np.cos(x) Element-wise cosine
np.log(x) Element-wise natural log
np.dot(x,y) Dot product
np.roots([1,0,-4]) Roots of a given polynomial coefficients](https://image.slidesharecdn.com/numpy-200828122621/85/Numpy-14-320.jpg)
Numpy
- 2. Topics Introduction of Numpy Indexing & slicing Mathematical computation Array comparison array Manipulation transpose & swapcase insert and remove
- 3. Topics What is Numpy? Why Numpy? What is Array? Dimensions in Arrays Initialization of an Array.
- 4. What is Numerical Python? NumPy is the fundamental package for scientific computing with Python. A powerful N-dimensional array object Sophisticated (broadcasting) functions Tools for integrating C/C++ and Fortran code Useful linear algebra, Fourier transform, and random number capabilities
- 5. Why NumPy? NumPy arrays are stored at one continuous place in memory unlike lists, so processes can access and manipulate them very efficiently. This behavior is called locality of reference in computer science. This is the main reason why Numpy is faster than lists. Also it is optimized to work with latest CPU architectures.
- 6. Arrays NumPy’s main object is the homogeneous multidimensional array. It is a table of elements (usually numbers), all of the same type, indexed by a tuple of positive integers. In NumPy dimensions are called axes. The number of axes is rank. NumPy’s array class is called ndarray. It is also known by the alias array.
- 7. Dimensions in Arrays A dimension in arrays is one level of array depth 1-D Arrays An array that has 0-D arrays as its elements is called uni-dimensional or 1-D array.These are the most common and basic arrays. import numpy as np arr = np.array([1, 2, 3, 4, 5]) print(arr)
- 9. 2-D Arrays An array that has 1-D arrays as its elements is called a 2-D array.These are often used to represent matrix or 2nd order tensors. import numpy as np arr = np.array([[1, 2, 3], [4, 5, 6]]) print(arr)
- 10. 3-D arrays An array that has 2-D arrays (matrices) as its elements is called 3-D array.These are often used to represent a 3rd order tensor. import numpy as np arr = np.array([[[1, 2, 3], [4, 5, 6]], [[1, 2, 3], [4, 5, 6]]]) print(arr)
- 11. INITIALIZTION np.array([1,2,3]) 1d array np.array([(1,2,3),(4,5,6)]) 2d array np.arange(start,stop,step) range array np.linspace(0,2,9) Add evenly spaced values btw interval to array of length np.zeros((1,2)) Create and array filled with zeros np.ones((1,2)) Creates an array filled with ones np.random.random((5,5)) Creates random array np.empty((2,2)) Creates an empty array
- 12. ARRAY PROPERTIES Syntax Description array.shape Dimensions (Rows,Columns) len(array) Length of Array array.ndim Number of Array Dimensions array.size Number of Array Elements array.dtype Data Type type(array) Type of Array
- 13. COPYING/SORTING np.copy(array) Creates copy of array array.sort() Sorts an array array.sort(axis=0) Sorts axis of array
- 14. Operations Operator Description np.add(x,y) x + y Addition np.substract(x,y) x – y Subtraction np.divide(x,y) x / y Division np.multiply(x,y) x @ y Multiplication np.sqrt(x) Square Root np.sin(x) Element-wise sine np.cos(x) Element-wise cosine np.log(x) Element-wise natural log np.dot(x,y) Dot product np.roots([1,0,-4]) Roots of a given polynomial coefficients